电动汽车PMSM退磁故障诊断及故障模式识别

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Abstract The local demagnetization fault and uniform demagnetization fault of permanent magnets easily appears in permanent magnet synchronous motor (PMSM) drive system of electric vehicle (EV) due to the influences of PMSM power density, control method and operation environment. In order to realize safe and reliable operation of PMSM drive system, the demagnetization fault diagnosis and fault mode recognition of PMSM has been one of the key technique problems which urgently need to be solved. Therefore, an algebraic identification method is first proposed in this paper to implement online identification of permanent magnet flux, then the identification results is used as the criterion of qualitative diagnosis of demagnetization fault, and then, the instantaneous frequency analysis method of stator current based on Hilbert-Hang transform (HHT) is adopted to realize the effective extraction of non-stationary characteristic signals of local demagnetization fault under the vehicle operating conditions. At last, the simulation and experimental research results are showed to confirm that the proposed integrated solutions of demagnetization fault diagnosis and fault mode recognition of permanent magnets are able to realize the signal of online accurate diagnosis of demagnetization fault and reliable recognition of fault mode by realizing the online accurate identification of permanent magnet flux and the effective extraction of non-stationary weak characteristic signals of local demagnetization fault under the constraints of measurement noise and vehicle operating conditions. Finally, recognition of demagnetization fault online diagnosis and fault mode can be achieved effectively.

Key words： Electric vehicle permanent magnet synchronous motor drive system algebraic identification method Hilbert-Huang transform demagnetization fault diagnosis fault mode recognition

Received: 14 October 2015 Published: 22 March 2017

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TM351

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	Li Hongmei
	Chen Tao

Cite this article:

Li Hongmei,Chen Tao. Demagnetization Fault Diagnosis and Fault Mode Recognition of PMSM for EV[J]. Transactions of China Electrotechnical Society, 2017, 32(5): 1-8.

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https://dgjsxb.ces-transaction.com/EN/ OR https://dgjsxb.ces-transaction.com/EN/Y2017/V32/I5/1

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